(533g) Addressing Temporal Variability in Metabolomics: A Dynamic Modeling Approach to Sphingolipid Biosynthesis in Arabidopsis thaliana

Sphingolipids play a vital role in plant development and stress responses, driving a growing interest in the regulatory mechanisms of the sphingolipid pathway. Moreover, the regulatory behavior of this pathway is not fully understood. In our preceding study, we endeavored to examine regulatory behavior of this pathway but at a steady state [1]. Here, we investigate the regulatory dynamics of the sphingolipid pathway, focusing on the dynamic de novo sphingolipid biosynthesis and homeostasis in Arabidopsis thaliana cell cultures. This aims to shed light on essential and time-dependent metabolic mechanisms. Nonetheless, detecting sphingolipids in metabolomics presents challenges due to temporal data variability, especially in plants. In this study, we utilized nitrogen-15 (¹⁵N) isotope labeling to generate temporal dynamic metabolomic data with significant variations. To accurately measure the turnover fluxes of sphingolipids, we developed a quantitative dynamic modeling approach, a regularized and constraint-based dynamic metabolic modeling framework, as detailed in our preprint [2]. This framework approach marks significant progress in predicting time-course metabolic changes following enzymatic disruptions with notable precision. It efficiently handles variations between samples, thus improving reliability. This method adeptly uses transient metabolomics data to unravel complex metabolic pathways, leading to experimentally testable hypotheses that could notably reduce the necessity for extensive future experimental efforts. Our study shows the delicate balance between the synthesis and breakdown of sphingolipids in cell cultures, highlighting their critical function in cellular homeostasis. We found a specific preference for de novo synthesis over recycling of sphingolipids before reaching the mid-exponential phase. Furthermore, despite the challenges of data variability, our analysis underscores the essential roles of enzymes like sphingoid-base hydroxylase, long-chain-base kinase, and glucosylceramide synthase. Interruptions in these enzymes significantly impact cell survival and programmed cell death, emphasizing their key role in maintaining the balance of sphingolipid metabolism. Therefore, this study not only deepens our understanding of sphingolipid metabolism but also illustrates the power of dynamic modeling in analyzing complex metabolic pathways.

References:

[1] A. Alsiyabi, A. G. Solis, E. B. Cahoon, and R. Saha, “Dissecting the regulatory roles of ORM proteins in the sphingolipid pathway of plants,” PLoS Comput Biol, vol. 17, no. 1, p. e1008284, Jan. 2021, doi: 10.1371/JOURNAL.PCBI.1008284.

[2] A. Osinuga, A. Gonzalez Solis, R. E. Cahoon, A. Al-Siyabi, E. B. Cahoon, and R. Saha, “Quantitative Dynamic Analysis of de novo Sphingolipid Biosynthesis in Arabidopsis thaliana”, doi: 10.1101/2023.12.08.570827.